Spatiotemporal sensitivity analysis of vertical transport of pesticides in soil

Abstract

Environmental fate and transport processes are influenced by many factors. Simulation models that mimic these processes often have complex implementations, which can lead to over-parameterization. Sensitivity analyses are subsequently used to identify critical parameters whose uncertainties can be further reduced or better described and prediction variability minimized. In this study, a variance decomposition based global sensitivity analysis technique (Sobol' method) is conducted based on estimated concentrations in vertical soil compartments using the Pesticide Root Zone Model (PRZM). Daily simulations are performed that explore the input parameter space. Estimated concentrations are compared to data collected over the course of a growing season from an experimental site in Georgia. Our results suggest that model sensitivity is conditional and should be examined at appropriate spatial and temporal resolution to avoid omitting important parameters. This approach can yield a better understanding about the interplay between sensitivity/uncertainty and model dynamics in non-monotonic, non-linear systems.

Keywords: Fate and transport; Global sensitivity analysis; Pesticides; Sobol’ sensitivity analysis; Vertical transport.

Fig. 1.

Category of commonly used sensitivity analysis methods.

Fig. 2.

Composition of matrices A, B and $\left(A_B^{\left(i\right)}\right)$.

Fig. 3.

Essential steps involved to estimate global sensitivity index. We identified important parameters as those whose total sensitivity analyses were different than zero, then explored the conditional results for this subset of variables based on time and depth.

Fig. 4.

Pesticide soil concentrations.

Fig. 5.

Boxplot of first (red) and total order (green) sensitivity indices.

Fig. 6.

Time series plots of the first (black) and total order (red) sensitivity indices for the top six influential parameters at two soil compartments (0–15 cm and 75–90 cm).

Fig. 7.

(a)Boxplots of first (red) and total order (green) sensitivity indices with and without pesticide applications. (7b) Boxplots of first (red) and total order (green) sensitivity indices with and without pesticide applications.

Fig. 8.

Boxplots of conditional Pearson correlation coefficients.